Affiliations: Department of ECE, The University of British Columbia,
Vancouver, BC, Canada V6T 1Z4 | Department of ECE, Concordia University, 1-445 de
Maisonneuve Blvd. West, H961-41, Montreal, Quebec, Canada H3G 1M8
Abstract: The subject of this paper is fuzzy linguistic hedging, used to
modify membership functions. Our investigation will exceed the traditional
definition given by Zadeh (and others), upon which our research is based. We
will present new and more general definitions for four of the most commonly
used hedges. These hedges are very, more or less, positively
and negatively. The effect of applying each hedge to a membership
function will be described both qualitatively and quantitatively in this paper.
We will also describe conditions under which a specific hedge is valid, chart
the examples, and explore the properties of the hedge operations. A software
program called FuzzyMarkx has been developed for understanding and applying the
above four hedges to list of data. It is specially designed for altering school
grade distributions. It allows users to view the new grades, the grade
distribution as well as the graphical representation of the hedge being
applied.
Keywords: fuzzy sets, fuzzy operations, linguistic hedges, FuzzyMarkx, very, more or less, positively, negatively
